MindRelax: Smart System for Emotion and Mental Stress Monitoring, Detection and Management DOI

Shivaani Dushya Rajkumar,

Ihill Ushan Dewpura,

Piyoshila Fernandez

et al.

Published: Dec. 7, 2023

Mental stress is a reaction, to pressures while emotions are personal responses specific events. Previous studies have shown that mental prevalent in Sri Lanka, where health concerns often go unnoticed. The World Health Organization estimates around 5% 10% of Lankas population faces issues emphasizing the need for support. This project aims develop smartphone application utilizes learning and machine techniques analyze text, facial expressions, speech patterns, heart rate fluctuations physical activity levels order detect manage individuals emotions. By utilizing this proposed Lankans will means effectively their improve well being. It also provide suggestions, activities can help alleviate stress. Index Terms; Heart Rate Variations (HRV) Convolutional Neural Network (CNN) Multi Layer Perceptron (MLP) Mel Frequency Cepstral Coefficients (MFCC) Long short term memory network (LSTM)

Language: Английский

A Survey on Sensor-Based Techniques for Continuous Stress Monitoring in Knowledge Work Environments DOI Open Access
ML Tlachac,

Elena Vildjiounaite,

Jaakko Tervonen

et al.

ACM Transactions on Computing for Healthcare, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 28, 2025

Prolonged work stress has an extensive negative impact across modern society. Recently, it become increasing issue, specifically in cognitively demanding knowledge-intensive professions. To address the global necessity of timely detection and reduction stress, sensor-based automated methods for measuring are emerging. Physiological behavioral sensor data enable potential continuous detection, but challenges still exist concerning effort required from user sufficiency available information, especially models that want to adapt personal traits perceptions. This survey paper focuses on recognition enabling unobtrusive monitoring knowledge environment, with a acceptance load suitable sustainable long-term adoption. We provide overview theoretical background review recent developments assessment, emphasizing real-world studies using physiological, behavioral, environmental data. In addition, we discuss applicability different methods, including acceptance. The presented provides insights into automating assessment related factors advance development personalized well-being solutions based pervasive

Language: Английский

Citations

0
Physiological Data-Based Stress Detection: From Wrist Sensors to Cloud Computing and User Feedback Integration DOI

G. R. Karpagam,

H. M.,

K. Kabilan

et al.

Published: June 28, 2024

Language: Английский

Citations

0
StressSense: An IoT-Enabled Platform for Stress Level Prediction, Prevention, and Methods There of DOI
Santhosh Phanitalpak Gandhala, Shubham Joshi, Sonali Das

et al.

Lecture notes in electrical engineering, Journal Year: 2024, Volume and Issue: unknown, P. 541 - 555

Published: Jan. 1, 2024

Language: Английский

Citations

0
Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications DOI Creative Commons

Jeyavijayan Rajendran,

Nimi Wilson Sukumari,

P. Subha Hency Jose

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(12), P. 1252 - 1252

Published: Dec. 11, 2024

A battery-operated biomedical wearable device gradually assists in clinical tasks to monitor patients’ health states regarding early diagnosis and detection. This paper presents the development of a self-powered portable electronic module by integrating an onboard energy-harvesting facility for electrocardiogram (ECG) signal processing personalized monitoring. The developed provides customizable approach power using lithium-ion battery, series silicon photodiode arrays, solar panel. new architecture techniques offered method include analog front-end unit, battery management unit acquiring real-time ECG signals. dynamic multi-level wavelet packet decomposition framework has been used applied extract desired features removing overlapped repeated samples from signal. Further, random forest with deep decision tree (RFDDT) designed offline classification, experimental results provide highest accuracy 99.72%. One assesses custom-developed sensor comparing its data those conventional biosensors. circuits are BQ25505 microprocessor support photodiodes cells which detect ambient light variations maximum 4.2 V supply enable continuous operation entire module. measurements conducted on each proposed demonstrate that signal-processing significantly reduces overlapping raw timing requirement criteria Also, it improves temporal requirements while achieving excellent classification performance at low computing cost.

Language: Английский

Citations

0
Detection and monitoring of stress using wearables: a systematic review DOI Creative Commons

Anuja Pinge,

Vinaya Gad,

Dheryta Jaisighani

et al.

Frontiers in Computer Science, Journal Year: 2024, Volume and Issue: 6

Published: Dec. 18, 2024

Over the last few years, wearable devices have witnessed immense changes in terms of sensing capabilities. Wearable devices, with their ever-increasing number sensors, been instrumental monitoring human activities, health-related indicators, and overall wellness. One area that has rapidly adopted is mental health well-being area, which covers problems such as psychological distress. The continuous capability allows detection stress, thus enabling early problems. In this paper, we present a systematic review different types sensors used by researchers to detect monitor stress individuals. We identify detail tasks data collection, pre-processing, features computation, training model explored research works. each step involved monitoring. also discuss scope opportunities for further deals management once it detected.

Language: Английский

Citations

0
MindRelax: Smart System for Emotion and Mental Stress Monitoring, Detection and Management DOI

Shivaani Dushya Rajkumar,

Ihill Ushan Dewpura,

Piyoshila Fernandez

et al.

Published: Dec. 7, 2023

Mental stress is a reaction, to pressures while emotions are personal responses specific events. Previous studies have shown that mental prevalent in Sri Lanka, where health concerns often go unnoticed. The World Health Organization estimates around 5% 10% of Lankas population faces issues emphasizing the need for support. This project aims develop smartphone application utilizes learning and machine techniques analyze text, facial expressions, speech patterns, heart rate fluctuations physical activity levels order detect manage individuals emotions. By utilizing this proposed Lankans will means effectively their improve well being. It also provide suggestions, activities can help alleviate stress. Index Terms; Heart Rate Variations (HRV) Convolutional Neural Network (CNN) Multi Layer Perceptron (MLP) Mel Frequency Cepstral Coefficients (MFCC) Long short term memory network (LSTM)

Language: Английский

Citations

0